Upload hitab.py

hitab.py

@@ -0,0 +1,47 @@
+"""HiTab : A Hierarchical Table Dataset for Question Answering and Natural Language Generation"""
+
+import json
+import datasets
+
+_CITATION = """\
+@article{cheng2021hitab,
+  title={HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation},
+  author={Cheng, Zhoujun and Dong, Haoyu and Wang, Zhiruo and Jia, Ran and Guo, Jiaqi and Gao, Yan and Han, Shi and Lou, Jian-Guang and Zhang, Dongmei},
+  journal={arXiv preprint arXiv:2108.06712},
+  year={2021}
+}
+"""
+_DESCRIPTION = """\
+HiTab is a dataset for question answering and data-to-text over hierarchical tables . It contains 10,672 samples and 3,597 tables from statistical reports (StatCan, NSF) and Wikipedia (ToTTo). 98.1% of the tables in HiTab are with hierarchies.
+"""
+
+_URL = "https://github.com/microsoft/HiTab"
+
+class HiTab(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "meaning_representation": datasets.Value("string"),
+                    "human_reference": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://www.microsoft.com/en-us/research/publication/hitab-a-hierarchical-table-dataset-for-question-answering-and-natural-language-generation/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": "train.jsonl"}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": "dev.jsonl"}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": "test.jsonl"}),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            for line in f.readlines():
+                j = json.loads(line)
+                yield example_idx, j